Artificial Intelligence in Education: Teacher Attitudes, Digital Competence, and Develeopment Needs

Abstract

The educational use of AI is increasingly encouraged both internationally and in Hungary, yet little empirical data is available on teachers’ attitudes and AI-use habits. This study aims to fill this gap by examining Hungarian teachers’ attitudes, digital competencies, institutional conditions, and developmental needs related to the integration of AI in education. Data were collected from 180 teachers across various school types using a questionnaire developed on the basis of international literature. Exploratory and confirmatory factor analyses identified five reliable factors measuring positive and negative attitudes, digital competence level, developmental needs, and institutional factors. The results show that digital competence predicts the frequency of AI use and also influences the development of attitudes. Regarding developmental needs, teachers report requiring further training and practical support materials, while among institutional factors, leadership attitude and support are the most decisive. Cluster analysis identified three teacher profiles based on attitudes, competence level, willingness to develop, and institutional factors. Each group requires different types of support, highlighting the need for differentiated professional development that focuses on competence building and strengthening the institutional environment.